Measuring spike pattern reliability with the Lempel-Ziv-distance

Markus Christen, Adam Kohn, Thomas Ott, Ruedi Stoop

Research output: Contribution to journalArticlepeer-review

17 Scopus citations


Spike train distance measures serve two purposes: to measure neuronal firing reliability, and to provide a metric with which spike trains can be classified. We introduce a novel spike train distance based on the Lempel-Ziv complexity that does not require the choice of arbitrary analysis parameters, is easy to implement, and computationally cheap. We determine firing reliability in vivo by calculating the deviation of the mean distance of spike trains obtained from multiple presentations of an identical stimulus from a Poisson reference. Using both the Lempel-Ziv-distance (LZ-distance) and a distance focussing on coincident firing, the pattern and timing reliability of neuronal firing is determined for spike data obtained along the visual information processing pathway of macaque monkey (LGN, simple and complex cells of V1, and area MT). In combination with the sequential superparamagnetic clustering algorithm, we show that the LZ-distance groups together spike trains with similar but not necessarily synchronized firing patterns. For both applications, we show how the LZ-distance gives additional insights, as it adds a new perspective on the problem of firing reliability determination and allows neuron classifications in cases, where other distance measures fail.

Original languageEnglish (US)
Pages (from-to)342-350
Number of pages9
JournalJournal of Neuroscience Methods
Issue number1-2
StatePublished - Sep 30 2006
Externally publishedYes


  • Clustering
  • Firing reliability
  • Lempel-Ziv-complexity
  • Macaque monkey
  • Neuron classification
  • Spike pattern
  • Spike train distance measure
  • Visual system

ASJC Scopus subject areas

  • General Neuroscience


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